```

=== "Python 3.8+"

    ```Python hl_lines="34"
    {!> ../../../docs_src/body_updates/tutorial002.py!}
    ```

### Using Pydantic's `update` parameter

Now, you can create a copy of the existing model using `.model_copy()`, and pass the `update` parameter with a `dict` containing the data to update.

!!! info

`33.2.0-android`. For more about depending on Guava, see
[using Guava in your build].

To add a dependency on Guava using Maven, use the following:

```xml
<dependency>
  <groupId>com.google.guava</groupId>
  <artifactId>guava</artifactId>
  <version>33.2.0-jre</version>
  <!-- or, for Android: -->
  <version>33.2.0-android</version>
</dependency>
```

To add a dependency using Gradle:

```gradle
dependencies {

```Python hl_lines="6"
{!../../../docs_src/path_operation_advanced_configuration/tutorial001.py!}
```

### Using the *path operation function* name as the operationId

If you want to use your APIs' function names as `operationId`s, you can iterate over all of them and override each *path operation's* `operation_id` using their `APIRoute.name`.

You should do it after adding all your *path operations*.

```Python hl_lines="2  12-21  24"

# Using Dataclasses

FastAPI is built on top of **Pydantic**, and I have been showing you how to use Pydantic models to declare requests and responses.

But FastAPI also supports using <a href="https://docs.python.org/3/library/dataclasses.html" class="external-link" target="_blank">`dataclasses`</a> the same way:

```Python hl_lines="1  7-12  19-20"
{!../../../docs_src/dataclasses/tutorial001.py!}
```

But Gunicorn supports working as a **process manager** and allowing users to tell it which specific **worker process class** to use. Then Gunicorn would start one or more **worker processes** using that class.

And **Uvicorn** has a **Gunicorn-compatible worker class**.

## Code Examples

[Using minio-go library](https://github.com/minio/minio/blob/master/docs/extensions/s3zip/examples/minio-go/main.go)
[Using AWS JS SDK v2](https://github.com/minio/minio/blob/master/docs/extensions/s3zip/examples/aws-js/main.js)
[Using boto3](https://github.com/minio/minio/blob/master/docs/extensions/s3zip/examples/boto3/main.py)

# FastAPI in Containers - Docker

When deploying FastAPI applications a common approach is to build a **Linux container image**. It's normally done using <a href="https://www.docker.com/" class="external-link" target="_blank">**Docker**</a>. You can then deploy that container image in one of a few possible ways.

Using Linux containers has several advantages including **security**, **replicability**, **simplicity**, and others.

!!! tip

Routes are declared in a single place, using functions declared in other places (instead of using decorators that can be placed right on top of the function that handles the endpoint). This is closer to how Django does it than to how Flask (and Starlette) does it. It separates in the code things that are relatively tightly coupled.

!!! check "Inspired **FastAPI** to"

   * SipHash-2-4 algorithm</a> using a seed value of {@code k = 00 01 02 ...}.
   *
   * @since 15.0
   */
  public static HashFunction sipHash24() {
    return SipHashFunction.SIP_HASH_24;
  }

  /**
   * Returns a hash function implementing the <a href="https://131002.net/siphash/">64-bit
   * SipHash-2-4 algorithm</a> using the given seed.
   *
   * @since 15.0
   */

                     TF_Status* status) {
  using tensorflow::NodeDef;
  using tensorflow::OpRegistrationData;
  using tensorflow::Tensor;
  using tensorflow::shape_inference::DimensionHandle;
  using tensorflow::shape_inference::InferenceContext;
  using tensorflow::shape_inference::ShapeAndType;
  using tensorflow::shape_inference::ShapeHandle;

  const int num_inputs = input_shapes->num_items;